code: def _set_up_model(self, config, pipeline, device):
      # get pretrained word vectors
      self._pretrain = (
          pipeline.foundation_cache.load_pretrain(
              config["pretrain_path"]
          )
          if "pretrain_path" in config
          else None
      )
      args = {
          "charlm_forward_file": config.get(
              "forward_charlm_path", None
          ),
          "charlm_backward_file": config.get(
              "backward_charlm_path", None
          ),
      }
      # set up trainer
      self._trainer = Trainer(
          pretrain=self.pretrain,
          model_file=config["model_path"],
          device=device,
          args=args,
          foundation_cache=pipeline.foundation_cache,
      )
      self._tqdm = "tqdm" in config and config["tqdm"]
  
file_path: stanza/stanza/pipeline/pos_processor.py
imports: import torch
  from stanza.models.common import doc
  from stanza.models.common.utils import unsort
  from stanza.models.common.vocab import VOCAB_PREFIX, CompositeVocab
  from stanza.models.pos.data import Dataset
  from stanza.models.pos.trainer import Trainer
  from stanza.pipeline._constants import *
  from stanza.pipeline.processor import UDProcessor, register_processor
  from stanza.utils.get_tqdm import get_tqdm
label_desc: Use image node_id 1 for calling the POSProcessor obj's underlying member method code with example usage: obj._set_up_model(config, pipeline, device) without return types